What is the difference between a receptive field and a feature map?
I hope this illustration will help you:



Receptive field(s): is a small portion of the input to produce only one node in a feature map.

Feature map(s): is a convolutional process output, a feature map can be said as a feature representation of filter's input. One feature map consists of many filter's outputs (from different receptive fields) from one kernel. The number of feature maps depends on the number of the kernel. 

So even feature maps are the next filter's input, but the next receptive fields is not a feature map. The next receptive field consists of a small portion node from different feature maps (not only one feature map).

And also, we can see from the illustration above, a feature map has two-dimensional size $(46 \times 46)$, then a receptive field size will always three-dimensional $(5 \times 5 \times \text{Number Of Feature Maps})$.